Systems for computer-aided diagnosis ("CAD") assist radiologists in the detection and classification of abnormal lesions in medical images. The purpose of such devices, as described in U.S. Pat. No. 5,815,591 to Roehrig, et. al., entitled "Method and Apparatus for Fast Detection of Spiculated Lesions in Digital Mammograms," the disclosure of which is hereby incorporated by reference in the present application, is to direct the attention of a radiologist to suspicious areas of the medical image that may reflect a threatening condition. While not a replacement for the experienced radiologist, CAD systems are designed to increase efficiency and reduce error, as a typical radiologist may be required to examine hundreds of medical images per day, which can lead to the possibility of a missed diagnosis due to human error.
Desired characteristics of a CAD system for analyzing mammograms include higher sensitivity, i.e., the ability to detect more subtle indications of abnormalities, coupled with lower false positive rates, i.e., the number of areas marked "suspicious" by the CAD system which, in reality, are not suspicious or indicative of a possibly cancerous condition. Generally speaking, it is desirable to minimize both the rate of false negatives, also called "misses", as well as the rate of false positives.
Today, conventional CAD systems usually treat each digital mammogram separately. In these systems, the plurality of mammograms that are usually taken of a woman's breasts--for example, the craniocaudal ("CC") and mediolateral oblique ("MLO") views of each of the left and right breasts, respectively--are digitized into digital mammograms and processed separately by the CAD system for detecting suspicious lesions. Suspicious lesions are located on each of the four images separately, without regard for what regions are found or not found in the other images. Although "mammogram" is sometimes used in the art to depict a set of four related films or views but sometimes used to depict one such view, for clarity purposes, the term "mammogram" shall correspond to a one of the related films or views taken during the mammography process.
However, in radiology practice it has been found that if the same abnormality appears in two different views of the same breast, then that abnormality has a higher probability of being a true lesion. This is because normal overlying tissue structures may accidentally appear to be an abnormal lesion in a single digital mammogram, tissue structures which will appear different or nonexistent in a different view. Accordingly, there is a lower probability of false positives when two different views of the same breast are examined, due to the lower probability of false or accidental crossing of tissue structure in the same region on two separate views of one breast.
Additionally, in radiology practice it has been found that if similar potentially suspicious structures are found in both the left and right breast, then those structures have a lower probability of being true lesions. Likewise, if a potentially suspicious structure is found in one breast but no corresponding structure is found in the opposite breast, there is a higher probability that the structure represents a true lesion. This is because normal tissue structure is usually similar between left and right breasts.
Moreover, if a breast develops a potentially suspicious lesion over a period of time as reflected by periodic mammograms of that breast, the likelihood increases that it is a true lesion. Accordingly, it is often useful to compare similar mammogram views of the same breast taken at different times, typically twelve months apart.
In comparing multiple views of a single breast or opposing breasts, it is necessary to have a common reference from which to measure the location of potentially suspicious lesions in each view. One such reference point is the nipple of the breast. A problem arises, however, in that the breast is often manipulated during the mammography process in various ways, such that the nipple may be in different and sometimes unpredictable locations in the digital mammogram. The nipple may, or may not, correspond to the location along the skin line furthest from the chest wall.
In "Computerized detection of masses in digital mammograms: Analysis of bilateral subtraction images," Med. Phys. 18 (5), September/October 1991, Yin and Giger et. al. disclose a bi-lateral subtraction technique, in which one image is rotated and translated to best match the other image, and then left and right images are subtracted from each other pixel-by-pixel. The resulting difference image is then thresholded to obtain several "starting points" which represent the areas of largest difference between left and right breasts. However, in the Yin and Giger et. al. disclosure, it is only raw pixels that are compared between left and right breasts, and the simple output obtained is only a starting point for further analysis.
In U.S. Pat. No. 5,579,360, Abdel-Mottaleb describes mass detection by computer using digital mammograms of the same breast taken from different viewing directions. Abdel-Mottaleb describes a method in which position, size, shape, intensity variance, and brightness are each directly compared between the two views of the same breast. The disclosed Abdel-Mottaleb method is disadvantageous, however, in that if any one such measure between views does not correlate within specified boundaries, the suspect spot is marked as a false positive, whereas correlated spots meeting all criteria lead directly to a mark on the output display directing the attention of the radiologist to that spot. Such a binary approach can often accord inordinate weight to the inter-view comparison process, at the expense of strong indicators that may still exist within a single view.
Accordingly, it would be desirable to provide a computer-aided diagnosis system that uses information from multiple digital mammograms to provide sensitive, fast, and reliable identification of suspicious, lesions in a digital mammogram.
It would be further desirable to provide a computer-aided diagnosis system that processes information from a first digital mammogram view of a breast, together with comparative information from a plurality of views of the same breast, to arrive at an overall suspiciousness determination regarding potentially suspicious lesions in the first digital mammogram view.
It would be further desirable to provide a computer-aided diagnosis system capable of locating the nipple in a digital mammogram in a reliable manner that accommodates different nipple locations corresponding to different breast manipulations that may take place during the mammography process.
It would be further desirable to provide a computer-aided diagnosis system that processes information from a first digital mammogram view of a breast, together with comparative information from a digital mammogram of the opposite breast, to arrive at an overall suspiciousness determination regarding potentially suspicious lesions in the first digital mammogram view.
It would be even further desirable to provide a computer-aided diagnosis system that processes information from a first digital mammogram view of a breast, together with comparative information from a digital mammogram of the same breast taken earlier in time, to arrive at an overall suspiciousness determination regarding potentially suspicious lesions in the first digital mammogram view.
It would be still further desirable to provide a computer-aided diagnosis system that processes information from a first digital mammogram view of a breast, together with comparative information from (a) a different digital mammogram view of the same breast, (b) a digital mammogram of the opposite breast, and (c) a digital mammogram of the same breast taken earlier in time, to arrive at an overall suspiciousness determination regarding potentially suspicious lesions in the first digital mammogram view.